Overview

Brought to you by YData

Dataset statistics

Number of variables16
Number of observations1035
Missing cells1932
Missing cells (%)11.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory129.5 KiB
Average record size in memory128.1 B

Variable types

Numeric16

Alerts

al2o3 is highly overall correlated with caot and 4 other fieldsHigh correlation
caot is highly overall correlated with al2o3 and 4 other fieldsHigh correlation
k2o is highly overall correlated with al2o3 and 2 other fieldsHigh correlation
mgo is highly overall correlated with na2oHigh correlation
na2o is highly overall correlated with al2o3 and 4 other fieldsHigh correlation
pf is highly overall correlated with al2o3 and 3 other fieldsHigh correlation
r1_iram1622 is highly overall correlated with r2_iram1622 and 1 other fieldsHigh correlation
r28_iram1622 is highly overall correlated with r2_iram1622 and 1 other fieldsHigh correlation
r2_iram1622 is highly overall correlated with r1_iram1622 and 3 other fieldsHigh correlation
r3_iram1622 is highly overall correlated with r1_iram1622 and 2 other fieldsHigh correlation
r7_iram1622 is highly overall correlated with r28_iram1622 and 2 other fieldsHigh correlation
sio2 is highly overall correlated with al2o3 and 4 other fieldsHigh correlation
r1_iram1622 has 638 (61.6%) missing values Missing
r2_iram1622 has 94 (9.1%) missing values Missing
r3_iram1622 has 898 (86.8%) missing values Missing
r7_iram1622 has 252 (24.3%) missing values Missing
r28_iram1622 has 50 (4.8%) missing values Missing

Reproduction

Analysis started2024-11-29 01:07:36.492401
Analysis finished2024-11-29 01:08:28.234668
Duration51.74 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

g45µ
Real number (ℝ)

Distinct219
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-7.6889649 × 10-16
Minimum-4.0751774
Maximum7.1879365
Zeros0
Zeros (%)0.0%
Negative565
Negative (%)54.6%
Memory size8.2 KiB
2024-11-28T20:08:28.389446image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-4.0751774
5-th percentile-1.1930338
Q1-0.62418965
median-0.11222993
Q30.41869127
95-th percentile1.7896056
Maximum7.1879365
Range11.263114
Interquartile range (IQR)1.0428809

Descriptive statistics

Standard deviation1.0004834
Coefficient of variation (CV)-1.3011939 × 1015
Kurtosis6.0808836
Mean-7.6889649 × 10-16
Median Absolute Deviation (MAD)0.5309212
Skewness1.3574915
Sum-8.0535578 × 10-13
Variance1.0009671
MonotonicityNot monotonic
2024-11-28T20:08:28.609586image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.3966519949 33
 
3.2%
-0.5862667078 32
 
3.1%
-0.2070372821 30
 
2.9%
0.3618068564 24
 
2.3%
-0.01742256927 18
 
1.7%
-0.7758814206 18
 
1.7%
0.1721921436 17
 
1.6%
0.1153077297 16
 
1.5%
-1.079264961 15
 
1.4%
0.7410362821 15
 
1.4%
Other values (209) 817
78.9%
ValueCountFrequency (%)
-4.075177424 1
0.1%
-3.695947998 1
0.1%
-3.411525929 1
0.1%
-3.146065331 1
0.1%
-2.292799123 1
0.1%
-2.179030296 1
0.1%
-2.027338525 1
0.1%
-2.008377054 1
0.1%
-1.761877927 1
0.1%
-1.742916456 1
0.1%
ValueCountFrequency (%)
7.187936518 1
0.1%
6.239862954 1
0.1%
4.817752608 1
0.1%
4.514369067 1
0.1%
4.324754355 1
0.1%
4.248908469 2
0.2%
3.81279463 1
0.1%
3.433565204 1
0.1%
2.959528422 1
0.1%
2.940566951 1
0.1%

sba
Real number (ℝ)

Distinct115
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.2683359 × 10-15
Minimum-4.4607416
Maximum4.1713564
Zeros0
Zeros (%)0.0%
Negative525
Negative (%)50.7%
Memory size8.2 KiB
2024-11-28T20:08:28.768103image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-4.4607416
5-th percentile-1.4997313
Q1-0.59637216
median-0.044319388
Q30.55792
95-th percentile1.6620256
Maximum4.1713564
Range8.632098
Interquartile range (IQR)1.1542922

Descriptive statistics

Standard deviation1.0004834
Coefficient of variation (CV)-7.8881581 × 1014
Kurtosis1.3267141
Mean-1.2683359 × 10-15
Median Absolute Deviation (MAD)0.55205278
Skewness0.32069312
Sum-1.3180568 × 10-12
Variance1.0009671
MonotonicityNot monotonic
2024-11-28T20:08:28.917518image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1062404596 28
 
2.7%
-0.3956257007 28
 
2.7%
0.3571735398 27
 
2.6%
0.4575467719 25
 
2.4%
0.05605384361 25
 
2.4%
-0.1446926205 25
 
2.4%
0.557920004 24
 
2.3%
-0.4458123167 24
 
2.3%
0.5077333879 24
 
2.3%
-0.5963721648 24
 
2.3%
Other values (105) 781
75.5%
ValueCountFrequency (%)
-4.460741599 1
0.1%
-3.457009279 1
0.1%
-2.80458327 1
0.1%
-2.704210038 1
0.1%
-2.654023422 1
0.1%
-2.453276958 1
0.1%
-2.403090342 1
0.1%
-2.352903726 2
0.2%
-2.252530494 2
0.2%
-2.152157262 2
0.2%
ValueCountFrequency (%)
4.171356358 1
0.1%
3.820050046 1
0.1%
3.76986343 1
0.1%
3.51893035 1
0.1%
3.418557118 1
0.1%
3.26799727 2
0.2%
3.01706419 1
0.1%
2.916690958 2
0.2%
2.866504342 1
0.1%
2.816317725 1
0.1%

pf
Real number (ℝ)

High correlation 

Distinct247
Distinct (%)23.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-6.8651472 × 10-18
Minimum-1.4970143
Maximum3.8117197
Zeros0
Zeros (%)0.0%
Negative589
Negative (%)56.9%
Memory size8.2 KiB
2024-11-28T20:08:29.051276image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-1.4970143
5-th percentile-1.1814523
Q1-0.88183915
median-0.4147617
Q31.0206471
95-th percentile1.4341815
Maximum3.8117197
Range5.308734
Interquartile range (IQR)1.9024862

Descriptive statistics

Standard deviation1.0004834
Coefficient of variation (CV)-1.4573372 × 1017
Kurtosis-1.1637623
Mean-6.8651472 × 10-18
Median Absolute Deviation (MAD)0.70631225
Skewness0.39423699
Sum1.7763568 × 10-14
Variance1.0009671
MonotonicityNot monotonic
2024-11-28T20:08:29.195804image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.8818391533 14
 
1.4%
-1.041329016 13
 
1.3%
-0.8476627541 13
 
1.3%
-0.6767807584 12
 
1.2%
-0.6539964923 12
 
1.2%
1.305450393 12
 
1.2%
-0.7337414236 12
 
1.2%
-0.9615840847 12
 
1.2%
-0.8020942219 12
 
1.2%
-0.824878488 11
 
1.1%
Other values (237) 912
88.1%
ValueCountFrequency (%)
-1.497014338 1
 
0.1%
-1.417269407 1
 
0.1%
-1.394485141 1
 
0.1%
-1.383093008 1
 
0.1%
-1.371700875 1
 
0.1%
-1.360308741 3
0.3%
-1.348916608 3
0.3%
-1.326132342 2
0.2%
-1.314740209 1
 
0.1%
-1.303348076 3
0.3%
ValueCountFrequency (%)
3.811719664 1
0.1%
3.777543265 1
0.1%
2.672506359 1
0.1%
2.421879432 1
0.1%
2.387703032 1
0.1%
2.22821317 1
0.1%
2.068723307 1
0.1%
1.96619411 2
0.2%
1.954801976 1
0.1%
1.806704247 1
0.1%

so3
Real number (ℝ)

Distinct59
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.0217859 × 10-15
Minimum-20.916707
Maximum3.6416369
Zeros0
Zeros (%)0.0%
Negative521
Negative (%)50.3%
Memory size8.2 KiB
2024-11-28T20:08:29.326292image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-20.916707
5-th percentile-1.15712
Q1-0.40437379
median-0.028000703
Q30.34837238
95-th percentile1.2893051
Maximum3.6416369
Range24.558344
Interquartile range (IQR)0.75274617

Descriptive statistics

Standard deviation1.0004834
Coefficient of variation (CV)-4.9485134 × 1014
Kurtosis184.72537
Mean-2.0217859 × 10-15
Median Absolute Deviation (MAD)0.37637308
Skewness-8.6028426
Sum-2.1067592 × 10-12
Variance1.0009671
MonotonicityNot monotonic
2024-11-28T20:08:29.476169image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1601858388 95
 
9.2%
-0.1220939736 74
 
7.1%
-0.2161872444 69
 
6.7%
0.2542791095 67
 
6.5%
-0.0280007028 66
 
6.4%
0.06609256798 65
 
6.3%
0.3483723803 56
 
5.4%
-0.3102805152 45
 
4.3%
-0.4043737859 44
 
4.3%
0.5365589219 40
 
3.9%
Other values (49) 414
40.0%
ValueCountFrequency (%)
-20.91670682 1
 
0.1%
-2.850798826 1
 
0.1%
-2.662612285 1
 
0.1%
-2.286239202 1
 
0.1%
-2.192145931 1
 
0.1%
-2.09805266 3
0.3%
-2.003959389 2
 
0.2%
-1.909866118 1
 
0.1%
-1.815772848 5
0.5%
-1.721679577 2
 
0.2%
ValueCountFrequency (%)
3.641636858 2
 
0.2%
3.171170504 1
 
0.1%
3.077077233 1
 
0.1%
2.982983962 1
 
0.1%
2.70070415 1
 
0.1%
2.512517608 3
0.3%
2.418424338 2
 
0.2%
2.230237796 6
0.6%
2.136144525 1
 
0.1%
2.042051254 3
0.3%

mgo
Real number (ℝ)

High correlation 

Distinct60
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1786325 × 10-17
Minimum-4.3491187
Maximum20.438363
Zeros0
Zeros (%)0.0%
Negative458
Negative (%)44.3%
Memory size8.2 KiB
2024-11-28T20:08:29.608842image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-4.3491187
5-th percentile-1.193305
Q1-0.56214231
median0.12639886
Q30.47066945
95-th percentile0.98707532
Maximum20.438363
Range24.787482
Interquartile range (IQR)1.0328118

Descriptive statistics

Standard deviation1.0004834
Coefficient of variation (CV)1.6192636 × 1016
Kurtosis169.10158
Mean6.1786325 × 10-17
Median Absolute Deviation (MAD)0.51640588
Skewness7.7323457
Sum6.750156 × 10-14
Variance1.0009671
MonotonicityNot monotonic
2024-11-28T20:08:29.751184image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4706694463 103
 
10.0%
0.8149400306 47
 
4.5%
-0.5047638761 41
 
4.0%
0.1837772926 41
 
4.0%
0.2411557234 41
 
4.0%
0.5854263077 34
 
3.3%
0.3559125848 32
 
3.1%
-0.5621423068 29
 
2.8%
0.7575615999 27
 
2.6%
0.06902043117 25
 
2.4%
Other values (50) 615
59.4%
ValueCountFrequency (%)
-4.349118735 6
 
0.6%
-2.857279536 1
 
0.1%
-1.59495406 1
 
0.1%
-1.480197198 1
 
0.1%
-1.422818768 1
 
0.1%
-1.365440337 5
 
0.5%
-1.308061906 13
1.3%
-1.250683476 19
1.8%
-1.193305045 15
1.4%
-1.135926614 13
1.3%
ValueCountFrequency (%)
20.43836334 1
 
0.1%
2.708428245 1
 
0.1%
2.421536091 1
 
0.1%
2.134643937 1
 
0.1%
1.56085963 2
 
0.2%
1.503481199 2
 
0.2%
1.388724338 3
0.3%
1.331345907 4
0.4%
1.273967476 5
0.5%
1.216589046 1
 
0.1%

sio2
Real number (ℝ)

High correlation 

Distinct324
Distinct (%)31.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.1821344 × 10-16
Minimum-2.799367
Maximum1.7714057
Zeros0
Zeros (%)0.0%
Negative510
Negative (%)49.3%
Memory size8.2 KiB
2024-11-28T20:08:29.908197image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-2.799367
5-th percentile-1.3446389
Q1-0.99171674
median0.15312839
Q30.87618847
95-th percentile1.4443071
Maximum1.7714057
Range4.5707727
Interquartile range (IQR)1.8679052

Descriptive statistics

Standard deviation1.0004834
Coefficient of variation (CV)1.0895979 × 1015
Kurtosis-1.4946725
Mean9.1821344 × 10-16
Median Absolute Deviation (MAD)0.9468644
Skewness-0.064937939
Sum9.8188124 × 10-13
Variance1.0009671
MonotonicityNot monotonic
2024-11-28T20:08:30.083879image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8417570414 19
 
1.8%
0.7556784601 16
 
1.5%
1.444307111 15
 
1.4%
0.7901098926 15
 
1.4%
1.039737779 14
 
1.4%
-0.991716742 13
 
1.3%
0.5835212973 12
 
1.2%
0.9622670554 12
 
1.2%
-1.103618898 11
 
1.1%
0.7642863182 11
 
1.1%
Other values (314) 897
86.7%
ValueCountFrequency (%)
-2.799366951 1
0.1%
-2.317326895 1
0.1%
-2.239856172 1
0.1%
-2.024659719 1
0.1%
-1.895541847 1
0.1%
-1.680345393 1
0.1%
-1.663129677 1
0.1%
-1.585658954 1
0.1%
-1.577051095 2
0.2%
-1.568443237 2
0.2%
ValueCountFrequency (%)
1.77140572 1
 
0.1%
1.762797862 2
0.2%
1.685327139 1
 
0.1%
1.650895706 2
0.2%
1.642287848 1
 
0.1%
1.63367999 1
 
0.1%
1.616464274 3
0.3%
1.599248558 1
 
0.1%
1.564817125 2
0.2%
1.556209267 4
0.4%

fe2o3
Real number (ℝ)

Distinct152
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.2563219 × 10-15
Minimum-9.2685631
Maximum2.5507387
Zeros0
Zeros (%)0.0%
Negative549
Negative (%)53.0%
Memory size8.2 KiB
2024-11-28T20:08:30.251312image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-9.2685631
5-th percentile-1.4613179
Q1-0.72938863
median-0.10589336
Q30.81579531
95-th percentile1.4935076
Maximum2.5507387
Range11.819302
Interquartile range (IQR)1.5451839

Descriptive statistics

Standard deviation1.0004834
Coefficient of variation (CV)-7.9635913 × 1014
Kurtosis6.0788291
Mean-1.2563219 × 10-15
Median Absolute Deviation (MAD)0.78614622
Skewness-0.61262312
Sum-1.2825296 × 10-12
Variance1.0009671
MonotonicityNot monotonic
2024-11-28T20:08:30.405090image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.1601103388 19
 
1.8%
1.113988701 19
 
1.8%
-0.5938461822 17
 
1.6%
1.141097191 17
 
1.6%
-0.2414358095 16
 
1.5%
-0.7022801431 16
 
1.5%
0.9242292697 15
 
1.4%
0.3820594654 15
 
1.4%
-0.7293886333 15
 
1.4%
-1.027582026 15
 
1.4%
Other values (142) 871
84.2%
ValueCountFrequency (%)
-9.26856305 1
 
0.1%
-2.84385087 1
 
0.1%
-2.247464085 1
 
0.1%
-2.220355595 1
 
0.1%
-2.057704654 1
 
0.1%
-1.895053712 1
 
0.1%
-1.813728242 2
0.2%
-1.786619752 3
0.3%
-1.759511261 3
0.3%
-1.705294281 2
0.2%
ValueCountFrequency (%)
2.550738682 2
0.2%
2.523630192 1
0.1%
2.496521702 2
0.2%
2.469413212 1
0.1%
2.388087741 1
0.1%
2.333870761 2
0.2%
2.306762271 1
0.1%
2.171219819 2
0.2%
2.144111329 2
0.2%
2.117002839 1
0.1%

caot
Real number (ℝ)

High correlation 

Distinct329
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9611899 × 10-15
Minimum-2.4597678
Maximum4.1433088
Zeros0
Zeros (%)0.0%
Negative515
Negative (%)49.8%
Memory size8.2 KiB
2024-11-28T20:08:30.550586image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-2.4597678
5-th percentile-1.4524148
Q1-0.87810064
median0.0074282449
Q30.83665183
95-th percentile1.4918408
Maximum4.1433088
Range6.6030767
Interquartile range (IQR)1.7147525

Descriptive statistics

Standard deviation1.0004834
Coefficient of variation (CV)2.5257144 × 1014
Kurtosis-0.71412889
Mean3.9611899 × 10-15
Median Absolute Deviation (MAD)0.84969824
Skewness0.04022317
Sum4.0905057 × 10-12
Variance1.0009671
MonotonicityNot monotonic
2024-11-28T20:08:30.709369image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.1973183183 17
 
1.6%
-0.7091847261 12
 
1.2%
0.5295319809 11
 
1.1%
0.8264144974 11
 
1.1%
-1.221051134 11
 
1.1%
-1.251763118 10
 
1.0%
-1.139152509 9
 
0.9%
-1.262000447 9
 
0.9%
-1.282475103 8
 
0.8%
-0.6477607572 8
 
0.8%
Other values (319) 929
89.8%
ValueCountFrequency (%)
-2.459767841 2
0.2%
-2.336919903 1
 
0.1%
-2.224309293 1
 
0.1%
-2.214071965 1
 
0.1%
-2.162885324 1
 
0.1%
-2.101461355 1
 
0.1%
-2.060512043 2
0.2%
-2.050274715 3
0.3%
-2.040037386 1
 
0.1%
-1.999088074 1
 
0.1%
ValueCountFrequency (%)
4.14330882 1
0.1%
3.498357146 1
0.1%
2.679370894 1
0.1%
2.443912346 1
0.1%
2.259640439 1
0.1%
1.92180861 1
0.1%
1.880859298 1
0.1%
1.860384641 1
0.1%
1.839909985 1
0.1%
1.829672657 2
0.2%

al2o3
Real number (ℝ)

High correlation 

Distinct200
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-6.8651472 × 10-18
Minimum-2.7302722
Maximum2.5829068
Zeros0
Zeros (%)0.0%
Negative608
Negative (%)58.7%
Memory size8.2 KiB
2024-11-28T20:08:30.892387image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-2.7302722
5-th percentile-1.4994199
Q1-0.71988011
median-0.26856761
Q31.0033131
95-th percentile1.5223225
Maximum2.5829068
Range5.313179
Interquartile range (IQR)1.7231932

Descriptive statistics

Standard deviation1.0004834
Coefficient of variation (CV)-1.4573372 × 1017
Kurtosis-0.83498934
Mean-6.8651472 × 10-18
Median Absolute Deviation (MAD)0.67696875
Skewness0.12246639
Sum1.0658141 × 10-14
Variance1.0009671
MonotonicityNot monotonic
2024-11-28T20:08:31.073580image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.49565399 24
 
2.3%
1.413597172 23
 
2.2%
-0.3301102201 18
 
1.7%
1.22896933 16
 
1.5%
-0.5762806754 16
 
1.5%
1.208455126 16
 
1.5%
-0.6173090846 15
 
1.4%
-0.4531954477 14
 
1.4%
-0.2890818109 14
 
1.4%
-0.3095960155 14
 
1.4%
Other values (190) 865
83.6%
ValueCountFrequency (%)
-2.730272159 1
0.1%
-2.586672727 1
0.1%
-2.566158523 1
0.1%
-2.545644318 1
0.1%
-2.504615909 1
0.1%
-2.42255909 1
0.1%
-2.278959658 1
0.1%
-2.258445453 1
0.1%
-2.237931249 1
0.1%
-2.217417044 2
0.2%
ValueCountFrequency (%)
2.582906835 1
 
0.1%
2.336736379 1
 
0.1%
2.213651152 1
 
0.1%
1.864909673 1
 
0.1%
1.823881264 1
 
0.1%
1.803367059 2
0.2%
1.782852855 2
0.2%
1.76233865 3
0.3%
1.741824446 3
0.3%
1.721310241 3
0.3%

na2o
Real number (ℝ)

High correlation 

Distinct19
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.8879155 × 10-16
Minimum-1.6756829
Maximum16.989771
Zeros0
Zeros (%)0.0%
Negative415
Negative (%)40.1%
Memory size8.2 KiB
2024-11-28T20:08:31.200709image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-1.6756829
5-th percentile-1.0923874
Q1-0.89795561
median0.26863526
Q30.85193069
95-th percentile1.0463625
Maximum16.989771
Range18.665454
Interquartile range (IQR)1.7498863

Descriptive statistics

Standard deviation1.0004834
Coefficient of variation (CV)-5.299408 × 1015
Kurtosis78.683784
Mean-1.8879155 × 10-16
Median Absolute Deviation (MAD)0.77772725
Skewness4.6240278
Sum-1.9539925 × 10-13
Variance1.0009671
MonotonicityNot monotonic
2024-11-28T20:08:31.319499image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
-1.092387425 229
22.1%
0.2686352567 187
18.1%
1.046362503 155
15.0%
-0.8979556134 117
11.3%
0.8519306918 98
9.5%
0.4630670684 64
 
6.2%
0.07420344504 48
 
4.6%
0.6574988801 45
 
4.3%
-0.7035238017 26
 
2.5%
1.240794315 19
 
1.8%
Other values (9) 47
 
4.5%
ValueCountFrequency (%)
-1.67568286 5
 
0.5%
-1.286819237 13
 
1.3%
-1.092387425 229
22.1%
-0.8979556134 117
11.3%
-0.7035238017 26
 
2.5%
-0.50909199 6
 
0.6%
-0.3146601783 5
 
0.5%
-0.1202283666 14
 
1.4%
0.07420344504 48
 
4.6%
0.2686352567 187
18.1%
ValueCountFrequency (%)
16.98977106 1
 
0.1%
2.212953374 1
 
0.1%
2.018521562 1
 
0.1%
1.435226127 1
 
0.1%
1.240794315 19
 
1.8%
1.046362503 155
15.0%
0.8519306918 98
9.5%
0.6574988801 45
 
4.3%
0.4630670684 64
 
6.2%
0.2686352567 187
18.1%

k2o
Real number (ℝ)

High correlation 

Distinct83
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5789839 × 10-16
Minimum-1.3091062
Maximum20.623727
Zeros0
Zeros (%)0.0%
Negative597
Negative (%)57.7%
Memory size8.2 KiB
2024-11-28T20:08:31.467019image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-1.3091062
5-th percentile-0.62211494
Q1-0.29134135
median-0.062344246
Q30.24298522
95-th percentile0.52287057
Maximum20.623727
Range21.932834
Interquartile range (IQR)0.53432657

Descriptive statistics

Standard deviation1.0004834
Coefficient of variation (CV)6.3362487 × 1015
Kurtosis349.09309
Mean1.5789839 × 10-16
Median Absolute Deviation (MAD)0.25444122
Skewness17.126549
Sum1.6342483 × 10-13
Variance1.0009671
MonotonicityNot monotonic
2024-11-28T20:08:31.601728image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.08778836837 40
 
3.9%
0.5228705704 38
 
3.7%
0.3702058357 36
 
3.5%
-0.01145600102 36
 
3.5%
-0.2404531031 33
 
3.2%
-0.2150089806 32
 
3.1%
-0.1641207357 30
 
2.9%
-0.2658972255 30
 
2.9%
-0.1132324908 28
 
2.7%
0.2938734684 28
 
2.7%
Other values (73) 704
68.0%
ValueCountFrequency (%)
-1.309106246 1
 
0.1%
-1.232773879 1
 
0.1%
-1.156441511 2
0.2%
-1.130997389 1
 
0.1%
-1.105553266 1
 
0.1%
-1.080109144 1
 
0.1%
-1.054665021 1
 
0.1%
-1.003776777 2
0.2%
-0.9783326541 4
0.4%
-0.9528885316 1
 
0.1%
ValueCountFrequency (%)
20.6237273 2
0.2%
4.492153672 1
 
0.1%
4.314044815 1
 
0.1%
2.329403264 1
 
0.1%
1.235305999 1
 
0.1%
0.955420652 1
 
0.1%
0.8536441622 2
0.2%
0.8282000398 1
 
0.1%
0.8027559173 1
 
0.1%
0.7773117949 3
0.3%

r1_iram1622
Real number (ℝ)

High correlation  Missing 

Distinct91
Distinct (%)22.9%
Missing638
Missing (%)61.6%
Infinite0
Infinite (%)0.0%
Mean18.253401
Minimum12.1
Maximum32.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-11-28T20:08:31.726207image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum12.1
5-th percentile14.6
Q116.9
median18.2
Q319.8
95-th percentile21.6
Maximum32.5
Range20.4
Interquartile range (IQR)2.9

Descriptive statistics

Standard deviation2.2066062
Coefficient of variation (CV)0.1208874
Kurtosis3.7181586
Mean18.253401
Median Absolute Deviation (MAD)1.4
Skewness0.48248014
Sum7246.6
Variance4.8691109
MonotonicityNot monotonic
2024-11-28T20:08:31.863442image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.4 13
 
1.3%
17.4 12
 
1.2%
18.1 11
 
1.1%
18.9 11
 
1.1%
16.9 10
 
1.0%
17.1 9
 
0.9%
19 9
 
0.9%
19.8 8
 
0.8%
20.4 8
 
0.8%
19.5 8
 
0.8%
Other values (81) 298
28.8%
(Missing) 638
61.6%
ValueCountFrequency (%)
12.1 2
0.2%
12.6 1
 
0.1%
13.2 2
0.2%
13.4 1
 
0.1%
13.7 3
0.3%
13.9 2
0.2%
14.1 1
 
0.1%
14.3 2
0.2%
14.5 4
0.4%
14.6 4
0.4%
ValueCountFrequency (%)
32.5 1
 
0.1%
23.6 1
 
0.1%
23.1 1
 
0.1%
22.8 1
 
0.1%
22.6 2
0.2%
22.3 3
0.3%
22.2 1
 
0.1%
22.1 2
0.2%
22 4
0.4%
21.9 1
 
0.1%

r2_iram1622
Real number (ℝ)

High correlation  Missing 

Distinct102
Distinct (%)10.8%
Missing94
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean31.154942
Minimum23.9
Maximum36.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-11-28T20:08:32.009680image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum23.9
5-th percentile27.9
Q129.9
median31.2
Q332.6
95-th percentile34.4
Maximum36.8
Range12.9
Interquartile range (IQR)2.7

Descriptive statistics

Standard deviation2.0374968
Coefficient of variation (CV)0.065398832
Kurtosis0.16559005
Mean31.154942
Median Absolute Deviation (MAD)1.3
Skewness-0.3025501
Sum29316.8
Variance4.1513931
MonotonicityNot monotonic
2024-11-28T20:08:32.154393image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
31.9 26
 
2.5%
32.1 25
 
2.4%
30.4 24
 
2.3%
30.9 21
 
2.0%
31.2 21
 
2.0%
30.7 21
 
2.0%
31.3 20
 
1.9%
32.3 20
 
1.9%
30.6 20
 
1.9%
31.6 20
 
1.9%
Other values (92) 723
69.9%
(Missing) 94
 
9.1%
ValueCountFrequency (%)
23.9 1
 
0.1%
24.7 1
 
0.1%
24.8 2
0.2%
24.9 1
 
0.1%
25.1 1
 
0.1%
25.4 1
 
0.1%
25.6 1
 
0.1%
25.8 3
0.3%
25.9 1
 
0.1%
26.1 2
0.2%
ValueCountFrequency (%)
36.8 1
 
0.1%
36.4 1
 
0.1%
36.3 2
 
0.2%
35.9 1
 
0.1%
35.7 2
 
0.2%
35.2 2
 
0.2%
35.1 5
0.5%
35 4
0.4%
34.9 6
0.6%
34.8 2
 
0.2%

r3_iram1622
Real number (ℝ)

High correlation  Missing 

Distinct78
Distinct (%)56.9%
Missing898
Missing (%)86.8%
Infinite0
Infinite (%)0.0%
Mean37.915328
Minimum30.1
Maximum48.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-11-28T20:08:32.330054image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum30.1
5-th percentile33.08
Q135.9
median38
Q339.6
95-th percentile41.84
Maximum48.4
Range18.3
Interquartile range (IQR)3.7

Descriptive statistics

Standard deviation2.8136979
Coefficient of variation (CV)0.074210035
Kurtosis1.0801332
Mean37.915328
Median Absolute Deviation (MAD)1.8
Skewness0.091001343
Sum5194.4
Variance7.9168957
MonotonicityNot monotonic
2024-11-28T20:08:32.525242image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39.6 5
 
0.5%
38 4
 
0.4%
34.8 4
 
0.4%
39.1 4
 
0.4%
36.9 4
 
0.4%
38.4 3
 
0.3%
35.9 3
 
0.3%
37.8 3
 
0.3%
40.1 3
 
0.3%
38.2 3
 
0.3%
Other values (68) 101
 
9.8%
(Missing) 898
86.8%
ValueCountFrequency (%)
30.1 1
0.1%
30.9 1
0.1%
31.8 2
0.2%
31.9 1
0.1%
32.9 1
0.1%
33 1
0.1%
33.1 1
0.1%
33.7 1
0.1%
34.1 2
0.2%
34.3 1
0.1%
ValueCountFrequency (%)
48.4 1
0.1%
44.3 1
0.1%
44.2 1
0.1%
43.3 1
0.1%
43.2 1
0.1%
42.2 1
0.1%
42 1
0.1%
41.8 1
0.1%
41.7 1
0.1%
41.6 2
0.2%

r7_iram1622
Real number (ℝ)

High correlation  Missing 

Distinct119
Distinct (%)15.2%
Missing252
Missing (%)24.3%
Infinite0
Infinite (%)0.0%
Mean47.466794
Minimum40
Maximum53.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-11-28T20:08:32.684731image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile43.2
Q145.8
median47.5
Q349.2
95-th percentile51.4
Maximum53.9
Range13.9
Interquartile range (IQR)3.4

Descriptive statistics

Standard deviation2.4508145
Coefficient of variation (CV)0.05163219
Kurtosis-0.12721189
Mean47.466794
Median Absolute Deviation (MAD)1.7
Skewness-0.16069357
Sum37166.5
Variance6.0064919
MonotonicityNot monotonic
2024-11-28T20:08:32.846991image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47.2 21
 
2.0%
47.9 18
 
1.7%
46.5 17
 
1.6%
46.8 17
 
1.6%
45.9 16
 
1.5%
48.6 15
 
1.4%
47.3 15
 
1.4%
47.1 15
 
1.4%
48.4 14
 
1.4%
47.5 14
 
1.4%
Other values (109) 621
60.0%
(Missing) 252
24.3%
ValueCountFrequency (%)
40 1
0.1%
40.3 2
0.2%
40.7 1
0.1%
40.8 1
0.1%
41 2
0.2%
41.3 1
0.1%
41.7 1
0.1%
41.8 1
0.1%
42 1
0.1%
42.1 1
0.1%
ValueCountFrequency (%)
53.9 1
 
0.1%
53.7 1
 
0.1%
53.4 1
 
0.1%
53.2 1
 
0.1%
53.1 1
 
0.1%
53 1
 
0.1%
52.7 4
0.4%
52.6 2
0.2%
52.5 3
0.3%
52.4 2
0.2%

r28_iram1622
Real number (ℝ)

High correlation  Missing 

Distinct104
Distinct (%)10.6%
Missing50
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean58.376548
Minimum52.2
Maximum64.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-11-28T20:08:32.993066image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum52.2
5-th percentile54.9
Q157.1
median58.4
Q359.8
95-th percentile61.5
Maximum64.3
Range12.1
Interquartile range (IQR)2.7

Descriptive statistics

Standard deviation2.0123269
Coefficient of variation (CV)0.034471495
Kurtosis-0.1337412
Mean58.376548
Median Absolute Deviation (MAD)1.4
Skewness-0.18383925
Sum57500.9
Variance4.0494596
MonotonicityNot monotonic
2024-11-28T20:08:33.142771image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57.4 25
 
2.4%
59.3 24
 
2.3%
57.9 24
 
2.3%
57.1 24
 
2.3%
59.4 23
 
2.2%
59 21
 
2.0%
58.7 21
 
2.0%
58.4 21
 
2.0%
59.9 20
 
1.9%
57.3 20
 
1.9%
Other values (94) 762
73.6%
(Missing) 50
 
4.8%
ValueCountFrequency (%)
52.2 1
 
0.1%
52.3 1
 
0.1%
52.9 1
 
0.1%
53.1 3
0.3%
53.2 1
 
0.1%
53.3 2
0.2%
53.4 3
0.3%
53.6 2
0.2%
53.7 1
 
0.1%
53.8 2
0.2%
ValueCountFrequency (%)
64.3 1
0.1%
64 1
0.1%
63.5 1
0.1%
63.4 1
0.1%
63.3 1
0.1%
63.2 1
0.1%
63.1 1
0.1%
63 2
0.2%
62.9 1
0.1%
62.8 2
0.2%

Interactions

2024-11-28T20:08:25.534370image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:37.611867image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:42.350119image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:48.496055image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:53.718680image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:58.051894image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:02.407495image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:06.892881image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:10.092994image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:12.225368image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:13.931381image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:15.743837image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:17.913184image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:19.784737image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:21.776328image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:23.413746image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:25.641220image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:37.913089image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:42.732029image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:48.758735image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:54.065783image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:58.294231image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:02.902287image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:07.159764image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:10.208812image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:12.316147image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:14.051070image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:15.851562image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:18.044378image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:19.885216image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:21.867665image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:23.545999image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:25.760205image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:38.193040image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:43.081807image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:49.013889image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
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2024-11-28T20:08:17.443275image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:19.595120image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:21.551757image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:23.205384image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:25.301843image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:27.409895image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:41.906425image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:48.151162image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:53.352635image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:07:57.794652image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:02.119770image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:06.668777image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:09.967295image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:12.125188image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:13.789040image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:15.594580image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:17.559457image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:19.685025image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:21.667431image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:23.300525image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-28T20:08:25.423515image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-11-28T20:08:33.610739image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
al2o3caotfe2o3g45µk2omgona2opfr1_iram1622r28_iram1622r2_iram1622r3_iram1622r7_iram1622sbasio2so3
al2o31.000-0.659-0.062-0.1210.5630.2700.717-0.6040.1560.1400.061-0.192-0.1600.2040.769-0.045
caot-0.6591.000-0.2140.134-0.631-0.483-0.6530.6210.0190.1280.0890.2740.323-0.213-0.7180.113
fe2o3-0.062-0.2141.0000.0080.0810.3840.081-0.282-0.211-0.136-0.1020.031-0.0920.1700.2640.066
g45µ-0.1210.1340.0081.000-0.118-0.209-0.1200.272-0.217-0.044-0.118-0.109-0.026-0.091-0.143-0.030
k2o0.563-0.6310.081-0.1181.0000.4290.468-0.4430.095-0.116-0.011-0.091-0.2350.1580.567-0.065
mgo0.270-0.4830.384-0.2090.4291.0000.502-0.492-0.084-0.093-0.0330.063-0.1570.3300.480-0.043
na2o0.717-0.6530.081-0.1200.4680.5021.000-0.5740.0700.1070.056-0.125-0.1390.3710.695-0.042
pf-0.6040.621-0.2820.272-0.443-0.492-0.5741.000-0.197-0.117-0.1320.0380.128-0.103-0.7500.026
r1_iram16220.1560.019-0.211-0.2170.095-0.0840.070-0.1971.0000.3330.7120.5050.458-0.0530.128-0.066
r28_iram16220.1400.128-0.136-0.044-0.116-0.0930.107-0.1170.3331.0000.5060.4920.6350.077-0.0030.108
r2_iram16220.0610.089-0.102-0.118-0.011-0.0330.056-0.1320.7120.5061.0000.7990.7390.137-0.0160.035
r3_iram1622-0.1920.2740.031-0.109-0.0910.063-0.1250.0380.5050.4920.7991.0000.6710.205-0.185-0.008
r7_iram1622-0.1600.323-0.092-0.026-0.235-0.157-0.1390.1280.4580.6350.7390.6711.0000.183-0.2630.088
sba0.204-0.2130.170-0.0910.1580.3300.371-0.103-0.0530.0770.1370.2050.1831.0000.2130.085
sio20.769-0.7180.264-0.1430.5670.4800.695-0.7500.128-0.003-0.016-0.185-0.2630.2131.000-0.047
so3-0.0450.1130.066-0.030-0.065-0.043-0.0420.026-0.0660.1080.035-0.0080.0880.085-0.0471.000

Missing values

2024-11-28T20:08:27.600401image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-11-28T20:08:27.901240image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-11-28T20:08:28.100318image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

g45µsbapfso3mgosio2fe2o3caotal2o3na2ok2or1_iram1622r2_iram1622r3_iram1622r7_iram1622r28_iram1622
03.812795-1.148425-0.9615840.0660931.3313461.0139140.680253-1.1391531.4135970.2686350.370206NaN31.3NaN50.161.8
14.248908-0.997865-1.246387-0.028001-0.2752501.409876-0.729389-1.0265420.8391990.8519310.03943219.132.237.949.460.5
24.248908-0.997865-0.9615840.1601860.8149401.5303860.382059-0.1973181.0648560.6574990.064876NaN32.0NaN47.461.5
34.514369-1.248798-0.802094-0.404374-0.2178721.263542-0.729389-0.3508780.8186850.6574990.064876NaN29.9NaN46.260.1
42.371723-1.349171-0.756526-0.310281-0.3900071.452915-0.512521-1.0470170.9622850.8519310.11576517.530.135.847.358.5
52.713029-0.395626-0.9046230.254279-0.3900071.401268-0.593846-0.8217950.9622850.8519310.192097NaN30.8NaN45.658.0
64.8177531.0597860.1548450.160186-0.3900071.2205030.5447100.1712251.1469130.6574990.013988NaN30.5NaN44.055.2
73.4335650.206614-0.5286831.007025-0.1604931.289366-0.702280-1.3848481.1879410.8519310.828200NaN31.2NaN44.157.3
81.916648-0.395626-0.8020940.254279-0.2752501.470131-0.864931-1.4360350.2032590.8519310.675535NaN30.4NaN46.057.0
92.959528-0.897492-0.813486-0.216187-0.5047641.2549340.354951-1.3234241.0648561.0463630.522871NaN30.2NaN44.957.5
g45µsbapfso3mgosio2fe2o3caotal2o3na2ok2or1_iram1622r2_iram1622r3_iram1622r7_iram1622r28_iram1622
10250.532460-0.1446931.6358220.630652-0.390007-0.862599-0.7293890.908313-0.658337-0.897956-0.03690016.129.7NaNNaNNaN
10260.741036-0.8473050.906726-0.216187-0.447385-0.673226-0.4583041.031161-0.637823-1.092387-0.189565NaN28.8NaNNaNNaN
1027-0.169114-0.1446931.305450-0.404374-0.390007-0.828167-0.6480631.051636-0.740394-1.092387-0.11323217.130.3NaNNaNNaN
1028-0.377691-0.5963720.849765-20.91670720.438363-0.776520-9.2685630.816177-0.63782316.9897714.314045NaNNaNNaNNaNNaN
1029-0.339768-0.6967450.997863-0.686654-0.562142-0.7937360.1380830.969737-0.760909-1.092387-0.24045314.7NaNNaNNaNNaN
1030-0.794843-0.5461861.020647-0.216187-0.504764-0.957285-0.1601100.724041-0.719880-1.092387-0.164121NaN29.7NaNNaNNaN
1031-0.112230-0.7971191.202921-0.780747-0.504764-1.008932-0.0516760.652380-0.760909-1.092387-0.164121NaN29.6NaNNaNNaN
1032-0.169114-0.2450661.009255-0.122094-0.275250-0.922854-0.4583040.867364-0.576281-0.897956-0.011456NaN30.4NaNNaNNaN
10331.404688-0.5963721.157353-0.216187-0.447385-0.991717-0.2414360.877601-0.699366-1.092387-0.16412115.728.3NaNNaNNaN
1034-0.8138040.0560540.6788830.348372-0.275250-0.957285-0.5938460.908313-0.596795-1.092387-0.062344NaNNaNNaNNaNNaN